About the job
We're looking for a Research Scientist to join a team that builds the science behind how Amazon supports its 1.5M+ employees - from forecasting demand across HR services to optimizing how work gets routed and assigned in real time. You'll own high-impact operations research and causal inference work that directly reduces costs and improves the employee experience at global scale.
Responsibilities
- Design and build simulation and optimization models that automate workforce scheduling, hiring, and task assignment across Amazon's HR contact centers and back-office operations
- Develop causal inference frameworks to measure the true impact of policy changes, product launches, and AI-driven initiatives on employee experience and operational efficiency
- Collaborate with senior leaders to translate complex analytical findings into actionable strategies that influence staffing, routing, and resource allocation decisions affecting thousands of associates
- Push the boundaries of what's possible by combining operations research with machine learning and generative AI to solve novel workforce optimization problems
Qualifications
Minimum
- PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience with statistical modeling / machine learning
- Knowledge of R, MATLAB, Python or similar scripting language
Preferred
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows
- Experience consulting with senior leadership and executives in a fast-paced environment